On robust experiment design for identifying locally affine Takagi-Sugeno models

On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix

“…The minimization of a measure on the FIM is an OED approach and is the focus of this contribution. Kroll and Du ¨rrbaum [13] and Du ¨rrbaum and Kroll [14] are motivations for this work. In Kroll and Du ¨rrbaum [13], the FIM is used to determine the optimum experiment design for the estimation of the parameters of a static TS model.…”

“…Only the determinant is used as a scalar measure on the FIM. In Du ¨rrbaum and Kroll [14], the aspect of using space-filling designs to remedy the effect of wrongly assumed partition parameters is introduced to static models. Although some of the aspects are already present in the static case this contribution addresses the dynamic case in a systematic way, analyzing the impact of different optimization procedures and FIM measures with respect to achievable uncertainty improvement as well as model prediction quality.…”

“…Parameter values determined in steps 2 & 3 can be used to initialize the nonlinear optimization. The partition parameters from clustering and the local model parameters from (14) are not optimal w.r.t. the recursive model evaluation.…”